Suo Kang
Papers
1
Total Citations
12
H-Index
1
About
Suo Kang is a rising researcher in intelligent robotics and optimization algorithms, with a primary focus on enhancing autonomous navigation in complex environments. His most-cited work, "Path Planning of Robot Based on Improved Multi-Strategy Fusion Whale Algorithm" (2024, 12 citations), addresses critical challenges in warehouse logistics and manufacturing automation. Kang’s major contribution lies in developing a novel hybrid optimization approach that fuses multiple strategies within the whale algorithm framework, significantly reducing path length and energy consumption for mobile robots operating in constrained spaces. This work directly tackles the persistent trade-off between computational efficiency and path optimality in dynamic industrial settings. By improving the whale algorithm’s exploration and exploitation capabilities, Kang has provided a practical solution for real-time robot navigation that outperforms traditional methods. His research bridges the gap between theoretical metaheuristic optimization and applied robotics, offering tangible benefits for smart logistics systems. As a young scholar, Kang’s early citation impact signals growing recognition, and his work is particularly relevant for researchers developing energy-efficient automation solutions for Industry 4.0 environments.
Research Focus
Key Achievements
Top Papers
- 1